Results 21 to 30 of about 20,798 (142)

Uncertainty‐Guided Selective Adaptation Enables Cross‐Platform Predictive Fluorescence Microscopy

Advanced Intelligent Discovery, EarlyView.
Deep learning models often fail when transferred to new microscopes. A novel framework overcomes this by selectively adapting the early layers governing low‐level image statistics, while freezing deep layers that encode morphology. This uncertainty‐guided approach enables robust, label‐free virtual staining across diverse systems, democratizing ...
Kai‐Wen K. Yang, Andrew Bai, Alexandra Bermudez, Yunqi Hong, Zoe Latham, Iris Sloan, Michael Liu, Vishrut Goyal, Cho‐Jui Hsieh, Neil Y. C. Lin   +9 more
wiley   +1 more source

Retinal Vessel Segmentation: A Comprehensive Review From Classical Methods to Deep Learning Advances (1982–2025)

Advanced Intelligent Systems, EarlyView.
Four decades of retinal vessel segmentation research (1982–2025) are synthesized, spanning classical image processing, machine learning, and deep learning paradigms. A meta‐analysis of 428 studies establishes a unified taxonomy and highlights performance trends, generalization capabilities, and clinical relevance.
Avinash Bansal, Jan Kubíček, Jana Bahrová, Alice Varyšová, Martin Augustýnek, Marek Penhaker, Juraj Timkovič   +6 more
wiley   +1 more source

ANK1 and EPB41 Variants and the Risk of Steroid‐Induced Osteonecrosis

Arthritis &Rheumatology, EarlyView.
Objective Steroid‐induced osteonecrosis of the femoral head (SONFH) is a refractory skeletal disorder influenced by genetic and environmental factors. However, conclusive pathogenic genetic evidence remains elusive due to the limited exploration of rare damaging variants. In this study, we aimed to identify rare variants associated with SONFH.
Shengbao Chen, Xianmin Zhu, Zhongzhong Chen, Wei Chen, Hussam Alkaissi, Zeng Zhang, Yun Gao, Junhui Yin, Xiangtian Yu, Qiong Fu, Youshui Gao, Zhenzhong Zhu, Qianying Cai, Pengwei Zhang, Weibin Chen, Xin Zhao, Xiaojin Wu, Karel Pacak, Dongxu Jin, Chunde Bao, Zhengping Zhuang, Changqing Zhang   +21 more
wiley   +1 more source

On the importance of including both sexes in animal studies – insights from home‐cage monitoring

Biological Reviews, EarlyView.
ABSTRACT A review of behavioural studies using home‐cage monitoring (HCM) systems revealed that over 61% of studies used only male subjects, with only 24% including both sexes, despite evidence of substantial behavioural differences between male and female animals. This bias could influence the outcomes of biomedical research.
Maša Čater, Adam Dušek, Aleksandra Bartelik, Silvia Mandillo, Elisabetta Golini, Mara Rigamonti, Rasneer Sonia Bains, Hamish Forrest, Marion Rivalan, Melissa Long, Anna Kiryk, Lars Lewejohann, Nuno Henrique Franco   +12 more
wiley   +1 more source

Evolution of statistical analysis in empirical software engineering research: Current state and steps forward

, 2019
Software engineering research is evolving and papers are increasingly based on empirical data from a multitude of sources, using statistical tests to determine if and to what degree empirical evidence supports their hypotheses.
Feldt, Robert, Furia, Carlo A., Gren, Lucas, Huang, Ziwei, Neto, Francisco Gomes de Oliveira, Torkar, Richard   +5 more
core   +1 more source

Predicting cervical cancer DNA methylation from genetic data using multivariate CMMP

Canadian Journal of Statistics, EarlyView.
Abstract Epigenetic modifications link the environment to gene expression and play a crucial role in tumour development. DNA methylation, in particular, is gaining attention in cancer research, including cervical cancer, the focus of this study.
Hang Zhang, Steven Chen, Raymond Balise, Jiming Jiang, Nagi Ayad, J. Sunil Rao   +5 more
wiley   +1 more source

Transcranial Magnetic Stimulation as a Translational Biomarker in Early‐Phase Anti‐Seizure Medication Development: A Randomized, Double‐Blind, Placebo‐Controlled Study in Generalized Epilepsy

Clinical Pharmacology &Therapeutics, EarlyView.
One‐third of epilepsy patients remain treatment‐resistant, underscoring the need for novel anti‐seizure medications (ASMs) and reliable biomarkers of central target engagement. Cortical hyperexcitability is a hallmark of epilepsy, making excitability a valuable pharmacodynamic biomarker for early‐phase drug development supporting go/no‐go decision ...
Catherine M. E. de Cuba, Titia Q. Ruijs, Annika A. de Goede, Robert J. Doll, Maria Juachon, Michel J. A. M. van Putten, Geert Jan Groeneveld, Jules A. A. C. Heuberger   +7 more
wiley   +1 more source

Detection of fast radio transients with multiple stations: a case study using the Very Long Baseline Array

, 2011
Recent investigations reveal an important new class of transient radio phenomena that occur on sub-millisecond timescales. Often transient surveys' data volumes are too large to archive exhaustively.
Adam T. Deller, Bannister, Bertail, Bhat, Bhattacharya, Bishop, Bower, Burke-Spolaor, Cordes, Croft, David R. Thompson, Deller, Deneva, Duin, Hall, Hessels, Kiri L. Wagstaff, Lazio, Lyne, Randall B. Wayth, Steven J. Tingay, Taylor, Taylor, von Korff, Walid A. Majid, Walter F. Brisken, Wasserman   +26 more
core   +1 more source

A Multivariate Mixed‐Effects Regression Framework for Ground Motion Modeling: Integrating Parametric and Machine Learning Approaches

Earthquake Engineering &Structural Dynamics, EarlyView.
ABSTRACT Multivariate ground motion models (GMMs) that capture the correlation between different intensity measures (IMs) are essential for seismic risk assessment. Conventional GMMs are often developed using a two‐stage approach, where separate univariate models with predefined functional forms are fitted first, and correlation is addressed in a ...
Sayed Mohammad Sajad Hussaini, Shaghayegh Karimzadeh, Paulo B. Lourenço   +2 more
wiley   +1 more source

Real‐Time Data‐Driven Fault Diagnosis of Photovoltaic Arrays Using an Edge‐Server Machine‐Learning Framework

Energy Science &Engineering, EarlyView.
A real‐time, data‐driven framework detects and classifies photovoltaic array faults using edge sensing and server‐side machine learning. Ensemble tree models achieve near‐perfect accuracy with low latency, enabling practical, low‐cost deployment for reliable PV monitoring and intelligent maintenance.
Premkumar Manoharan, Sowmya Ravichandran, Deepak Kumar Sinha, Chandran Ramakrishnan, Omar Almomani   +4 more
wiley   +1 more source